Image-producing perfusion measurements of organs represent an important tool in medical diagnosis. This applies particularly to the measurement of cerebral perfusion parameters which are used to present acute cerebral perfusion disorders, for example in the diagnosis of ischemic cerebral infarct. When measuring perfusion parameters, for example cerebral blood flow (CBF) or cerebral blood volume (CBV), several tomographic images of the same examination volume, generally sectional images of a predetermined layer of the brain, are taken in chronological succession following injection of a contrast medium bolus and are analyzed to determine the perfusion parameters.
Most imaging methods for determining brain perfusion parameters use tracer-kinetic models with which the perfusion parameters from the image data of the image are calculated in order then to present the perfusion parameters in image form. These perfusion parameter images then make it possible, for example, to assess the degree of severity and extent of ischemia.
Examples of models used, and the determination of various perfusion parameters in cerebral perfusion computed tomography, are set out in the publications by M. König et al., “CT-Perfusionsbildgebung beim akuten ischämischen Hirninfarkt: Vergleich von Parameter-bildern der zerebralen Perfusion und Nativ-CT-Befunden”, [CT perfusion imaging in acute ischemic cerebral infarct: Comparison of parameter images of cerebral perfusion and native CT findings], Fortschr Röntgenstr 2000, 172, pages 219-226, and M. König et al., “Zerebrale Perfusions-CT: Theoretische Grundlagen, methodische Realisierung und praktische Erfahrungen in der Diagnostik des ischämischen Hirninfarktes” [Cerebral perfusion CT: Theoretical principles, methodology and practical experience in diagnosis of ischemic cerebral infarct], Fortschr Röntengstr 2000, 172, pages 210-218. The perfusion computed tomography used here has the advantage, compared to other imaging methods, that changes in concentration of the contrast medium in the vessel system are reflected directly in a proportional change of the CT values.
Nowadays, in addition to simple sectional images of the brain, it is possible, using multisection computed tomography, to measure larger volume areas of the brain or of other organs by simultaneous recording of several parallel sections.
The need to use models to determine the perfusion parameters from the image data often leads to methodology problems, since either it is not possible to produce an optimal injection bolus, or one of the parameters needed for the determination cannot be recorded with sufficient absolute accuracy. Although the perfusion parameter images obtained do then correctly reflect the relative perfusion conditions within the measured examination volume, they are associated with a patient-dependent, systematic error, which makes determination of the absolute values difficult. This is not an actual limitation for clinical diagnosis, because the image impression in most cases already permits adequate diagnosis, and relative values permit a quantitative analysis (cf. M. König et al.; “Quantitative Assessment of the Ischemic Brain by Means of Perfusion-Related Parameters Derived from Perfusion CT”; Stroke 2001; 32: 431-437).-However, a calibration to physiological normal values is desirable because, among other things, it permits normalized color image presentation, which greatly increases acceptance by users, for example neurologists.
In a known technique for calibration of perfusion parameter images, an ROI (region of interest) is placed manually in an anatomically coherent region of known tissue composition, and the perfusion parameter value in this ROI is determined. From the relationship of this value and an assumed physiological normal value for this tissue composition it is possible to determine, for the entire image, a calibration factor with which all perfusion parameter values of the image are scaled.
However, this procedure has some disadvantages. Thus, the ROI has to be positioned manually and its size must be adapted in order to obtain an image area of homogeneous composition. Because of the substantial layer thicknesses which are needed for adequate contrast in image-producing perfusion measurements, there are only a few areas of really homogeneous tissue composition. This applies above all to the gray matter of the brain, in respect of which corresponding ROIs must be chosen very small. Although larger cerebral medulla areas can be selected, these have lower perfusion parameter values, with the result that they produce more noise. In elderly patients, the values in these areas are also much more variable.